In recent years, optical computing techniques have been developed for applications in the Oil and Gas Industry in the form of optical sensors on downhole or surface equipment to evaluate a variety of fluid properties. An optical computing device is a device configured to receive an input of electromagnetic radiation from a substance or sample of the substance and produce an output of electromagnetic radiation from a processing element, also referred to as an optical element. The optical element may be, for example, a narrow band optical filter or an Integrated Computational Element (“ICE”) (also known as a Multivariate Optical Element (“MOE”).
Fundamentally, optical computing devices utilize optical elements to perform calculations, as opposed to the hardwired circuits of conventional electronic processors. When light from a light source interacts with a substance, unique physical and chemical information about the substance is encoded in the electromagnetic radiation that is reflected from, transmitted through, or radiated from the sample. Thus, the optical computing device, through use of the optical element and one or more detectors, is capable of extracting the information of one or multiple characteristics/properties or analytes within a substance and converting that information into a detectable output signal reflecting the overall properties of a sample.
The characteristic or analyte of interest is directly related to the intensity of the light transmitted both through the sample and through the ICE. This light is generally referred to as the “A” Channel. One challenge in optical computing or ICE computing devices is that the light intensity in the A Channel may fluctuate. Such fluctuations might occur for a variety of reasons, including weakening of the bulb over time, in response to analyte concentration variations, or other spurious effects such as dust and dirt accumulation on the optical elements and windows. These spurious effects will cause the A Channel light intensity to be incorrect and, therefore, introduce negative factors into the accuracy of the optical device.
Conventional methods to provide sufficient solutions to the light fluctuation problem normalize or ratio out the spurious effects using a second “B” Channel. Thus, if the intensity of the light source were to be halved, then the assumption has been that the A Channel intensity would also be halved (thus creating an error), and the B Channel would be halved as well; thus, the A/B ratio remains the same. However, through our work in this area, it has been discovered that this assumption is incorrect. In other words, the light A/B ratio does not remain the same. Rather, it is now understood that when the light source intensity is halved, the A/B ratio does not remain the same and, thus, an error is introduced using conventional methods. This is especially troubling given that optical computing devices often have very low sensitivities, and even a one percent error in the A/B ratio could result in an error factor of 2, 3 or even 10 in the measured concentration value.
Accordingly, there is a need in the art for an optical computing device and method that overcomes the shortcomings of conventional normalization techniques to combat the effects of light fluctuation, thus providing a more reliable and accurate optical computing device.